Search Results (3,544)

Shallot (Allium hirtifolium Boiss.) is of considerable nutritional and medical significance due to its strong antioxidant properties; however, no nanophytotoxicity studies have assessed whether the use of nanofertilizers would improve shallot performance, micronutrient iron (Fe) enrichment, and yield in semi-arid regions. Herein, we evaluated the effects of magnetite nanoparticles (nFe₃O₄) on shallot grown for a full lifecycle in two semi-arid regions through bulb-priming followed by foliar application and compared them with conventional ferrous sulfate (FeSO₄) fertilizer and untreated control. Our results showed remarkable cellular adaptations to semi-arid climate upon nFe₃O₄ treatment as leaves displayed thickened cell walls, distinct chloroplasts featuring organized thylakoid grana and stroma, normal mitochondria, abundant starch grains, and plastoglobuli around chloroplasts compared to FeSO₄ or untreated control. At 900 mg/L nFe₃O₄, chlorophyll-a, chlorophyll-b, and carotenoid increased by 27–55%, 108–126%, and 77–97%, respectively, compared to FeSO₄ applied at recommended field rate (1800 mg/L). Significant increments in bulb diameter (38–39%) and sister bulb number (300–500%) were observed upon 900 mg/L nFe₃O₄ treatment compared to FeSO₄ (1800 mg/L) and control. Furthermore, with 900 mg/L nFe₃O₄ treatment, total phenol, flavonoids, and Fe in bulbs increased by 27–46%, 29–73%, and 486–549%, respectively, compared to FeSO₄ (1800 mg/L). These findings demonstrate that bulb-priming followed by foliar application of 900 mg/L of nFe₃O₄ could significantly promote cellular adaptation, thereby improving photosynthetic efficiency, bulb yield, antioxidant activities, and Fe biofortification in shallot, and may serve as a novel approach for improving shallot production in semi-arid regions. Full article

Background: Metabolic syndrome, a clinical condition defined by central obesity, impaired glucose regulation, elevated blood pressure, hypertriglyceridemia, and low high-density lipoprotein cholesterol across the lifespan, is now a major public health issue typically managed with lifestyle, behavioral, and dietary recommendations. However, “one-size-fits-all” recommendations often yield modest, heterogeneous responses and poor long-term adherence, creating a clinical need for more targeted and implementable preventive and therapeutic strategies. Objective: To synthesize evidence on how the gut microbiome can inform precision nutrition and exercise approaches for metabolic syndrome prevention and management, and to evaluate readiness for clinical translation. Key findings: The gut microbiome may influence cardiometabolic risk through microbe-derived metabolites and pathways involving short-chain fatty acids, bile acid signaling, gut barrier integrity, and low-grade systemic inflammation. Diet quality (e.g., Mediterranean-style patterns, higher fermentable fiber, or lower ultra-processed food intake) consistently relates to more favorable microbial functions, and intervention studies show that high-fiber/prebiotic strategies can improve glycemic control alongside microbiome shifts. Physical exercise can also modulate microbial diversity and metabolic outputs, although effects are typically subtle and may depend on baseline adiposity and sustained adherence. Emerging “microbiome-informed” personalization, especially algorithms predicting postprandial glycemic responses, has improved short-term glycemic outcomes compared with standard advice in controlled trials. Targeted microbiome-directed approaches (e.g., Akkermansia muciniphila-based supplementation and fecal microbiota transplantation) provide proof-of-concept signals, but durability and scalability remain key limitations. Conclusions: Microbiome-informed personalization is a promising next step beyond generic guidelines, with potential to improve adherence and durable metabolic outcomes. Clinical implementation will require standardized measurement, rigorous external validation on clinically meaningful endpoints, interpretable decision support, and equity-focused evaluation across diverse populations. Full article

Purpose: The effectiveness and feasibility of cancer prehabilitation have been well-validated in surgical settings, but its role in non-surgical treatments, such as chemotherapy and radiotherapy (RT), remains unclear. This scoping review aims to systematically explore the existing literature on prehabilitation programs for non-surgical cancer treatments. Methods: Following the scoping review methodology developed by the Joanna Briggs Institute, seven databases were systematically searched from their inception to October 2024 for peer-reviewed studies involving prehabilitation prior to non-surgical treatment. Data were extracted and reported adhering to PRISMA-ScR guidelines, using a convergent synthesis design to present qualitative and quantitative evidence. No formal risk-of-bias or quality appraisal was conducted. Results: Of 22,122 studies, 39 met the inclusion criteria, yielding a combined sample of 6073 patients and thirty-four unique interventions. Sample sizes ranged from 9 to 1992, with randomized control trials being the most common (16). Head and neck cancer was the most frequently studied, followed by breast, esophageal/gastric, and lung cancer. Of the included interventions, 23 were unimodal and 16 were multimodal. Exercise was the most common component (30), with nutrition (13), psychosocial (10), and educational (8) components also present. Most efficacy studies (84%) reported improved outcomes and nearly all (93%) feasibility studies found prehabilitation acceptable and implementable. Conclusions: This review highlights a growing body of literature examining prehabilitation prior to chemotherapy or RT in adult cancer patients, with studies suggesting potential benefits and feasibility. However, long-term trials, especially in diverse cancers and older populations, remain scarce. Our results provide insight into future implementation, evaluation of outcomes, and directions for future prehabilitation research. Full article

The agricultural industry faces increasing environmental degradation due to the intensive use of conventional chemical fertilizers, leading to water pollution and alterations in soil composition. In addition, root-knot and cyst nematodes are major constraints to cucumber production, causing severe root damage and yield losses worldwide, underscoring the need for sustainable alternatives to conventional fertilization and pest management. Under greenhouse conditions, a four-month cultivation trial evaluated vegetable oil-, micronutrient-, and activated flavonoid-based biostimulants, applying Key Eco Oil^® (Miami, USA) via soil drench (every 15 days) combined with foliar sprays of CropBioLife^® (Victoria, Australia) and KeyPlex 120^® (Miami, USA) (every 7 days). Results showed reduced parasitic nematodes by 66% in soil and decreased gall formation by 41% in roots. Chlorophyll fluorescence and infrared gas analysis revealed higher oxygen-evolving complex efficiency (38%), increased PSII electron transport, improved the fluorescence decrease ratio, also known as the vitality index (Rfd), and higher CO₂ assimilation compared to conventional treatments. Processed cucumbers showed higher sugar and nearly double ascorbic acid content, with improved flesh consistency and color. Therefore, the application of these bioactive products significantly reduced nematode infestation while enhancing plant growth and physiological performance, underscoring their potential as sustainable tools for crop cultivation and protection. These results provide evidence that sustainable bioactive biostimulants improve plant resilience, productivity, and nutritional quality, offering also an environmentally sound approach to pest management. Full article

Mechanical deep fertilization is an efficient fertilization method. However, the effects of different types of nitrogen fertilizer on rice grain yield and nitrogen use efficiency under deep-application conditions remain unclear. In this study, field experiments were carried out in 2021 and 2022. The experimental treatments consisted of three types of nitrogen fertilizer, i.e., urea (T1), slow/controlled-release fertilizer (T2), and super rice special fertilizer (T3), applied at a rate of 150 kg N ha⁻¹ via mechanical deep placement using Meixiangzhan 2 (MX) and Y liangyou 1378 (YL) as experimental materials. No fertilizer application was used as a control (T0) to calculate nitrogen use efficiency. The T2 treatment produced 29.03% and 25.52% higher grain yield for MX and YL because of the increase in productive panicles per ha and spikelet number per panicle, 21.20% and 13.68% higher nitrogen recovery efficiency, and 24.57% and 23.29% higher nitrogen agronomy efficiency than T1, respectively. In addition, the T2 treatment significantly improved the leaf area index and total aboveground biomass at the panicle initiation and heading stages. We also found that the POD, CAT, NR, and GOGAT of T2 for MX and YL at the heading stage were significantly enhanced compared to other treatments. Significant interaction was also observed in spikelet per panicle and 1000-grain weight between rice variety and nitrogen fertilizer type. Therefore, slow/controlled-release fertilizer application at the rate of 150 kg N per ha is a more feasible nitrogen fertilizer management strategy under mechanical deep placement, with the merit of increasing grain yield and improving nitrogen use efficiency in South China. Full article

Climate change poses a threat to global rice production by increasing the frequency and intensity of extreme weather events. The widespread cultivation of genetically uniform modern varieties has narrowed the genetic base of rice, increasing its vulnerability to these increased pressures. Rice landraces are traditional rice varieties that have been cultivated by farming communities for centuries and are considered crucial resources of genetic diversity. These landraces are adapted to a wide range of agro-ecological environments and exhibit valuable traits that provide tolerance to various biotic stresses, including drought, salinity, nutrient-deficient soils, and the increasing severity of climate-related temperature extremes. In addition, many landraces possess diverse alleles associated with resistance to biotic stresses, including pests and diseases. In addition, rice landraces exhibit great grain quality characters including high levels of essential amino acids, antioxidants, flavonoids, vitamins, and micronutrients. Hence, their preservation is vital for maintaining agricultural biodiversity and enhancing nutritional security, especially in vulnerable and resource-limited regions. However, rice landraces are increasingly threatened by genetic erosion due to widespread adoption of modern high-yielding varieties, habitat loss, and changing farming practices. This review discusses the roles of rice landraces in developing resilient and climate-smart rice cultivars. Moreover, the Pantiange Heigu landrace, cultivated at one of the highest altitudes globally in Yunnan Province, China, has been used as a case study for integrated conservation by demonstrating the successful combination of in situ and ex situ strategies, community engagement, policy support, and value-added development to sustainably preserve genetic diversity under challenging environmental and socio-economic challenges. Finally, this study explores the importance of employing advanced genomic technologies with supportive policies and economic encouragements to enhance conservation and sustainable development of rice landraces as a strategic imperative for global food security. By preserving and enhancing the utilization of rice landraces, the agricultural community can strengthen the genetic base of rice, improve crop resilience, and contribute substantially to global food security and sustainable agricultural development in the face of environmental and socio-economic challenges. Full article

This study was conducted to evaluate the effect of rumen-protected γ-aminobutyric acid (GABA) supplementation on milk productivity of lactating Holstein cows. Eighteen Holstein dairy cows (mean parity, 2.2 ± 1.0 year; mean milk yield, 34.3 ± 5.5 kg) were selected in a commercial dairy farm for the experiment. The experiment was conducted from 17 July 2024 to 11 September 2024 (56 days). Generally, THI 72 is set as a threshold since the productivity of Holstein cows starts to decrease. Animals were exposed to heat stress conditions (THI ≥ 72) during the experimental period. The basal diet was fed as a total mixed ration (TMR), and GABA was top-dressed onto the TMR. The treatments were basal diet (Control), basal diet supplemented with rumen-protected GABA 3 g/d (Treatment 1), and basal diet supplemented with rumen-protected GABA 6 g/d (Treatment 2) as a completely randomized design. Statistical significance was compared between the control and GABA treatment groups using the method of repeated measurement. Increased levels of rumen-protected GABA supplementation tended to mitigate the decline in milk yield associated with heat stress (p = 0.083). Milk fat content in the GABA supplementation groups was significantly greater than that in the control group (p = 0.036). Milk lactose content was significantly increased by GABA supplementation (p = 0.017). Blood metabolic profiles and cortisol did not differ significantly between the control and GABA supplementation groups. Activities in the GABA supplementation groups were significantly greater than those in the control group (p < 0.05). Rest and rumination times in the GABA supplementation group were significantly lower than those in the control group (p < 0.05). These results suggest that rumen-protected GABA can be a practical nutritional intervention for minimizing productivity losses in Holstein cows during periods of elevated ambient temperature. Full article

Elevated atmospheric CO₂ is known to alter plant physiology, yet its specific effects on nutrient-rich leafy vegetables remain insufficiently quantified. This study aimed to examine how eCO₂ influences yield and nutritional quality in kale (Brassica oleracea) and spinach (Spinacia oleracea) through the first meta-analysis focused exclusively on these crops. Following the Collaboration for Environmental Evidence (CEE) guidelines, we systematically reviewed eligible studies and conducted a random-effects meta-analysis to evaluate overall and subgroup responses based on CO₂ concentration, crop type and exposure duration. Effect sizes were calculated using Hedges’ g with 95% confidence intervals. The analysis showed that eCO₂ significantly increased biomass in spinach (g = 1.21) and kale (g = 0.97). However, protein content declined in both crops (spinach: g = −0.76; kale: g = −0.61), and mineral concentrations, particularly calcium and magnesium, were reduced, with spinach exhibiting stronger nutrient losses overall. The variability in response across different CO₂ concentrations and exposure times further underscores the complexity of eCO₂ effects. These results highlight a trade-off between productivity and nutritional quality under future CO₂ conditions. Addressing this challenge will require strategies such as targeted breeding programmes, biofortification, precision agriculture and improved sustainable agricultural practices to maintain nutrient density. This research provides critical evidence for policymakers and scientists to design sustainable food systems that safeguard public health in a changing climate. Full article

Diabetes develops through a mix of clinical, metabolic, lifestyle, demographic, and environmental factors. Most current classification models focus on traditional biomedical indicators and do not include environmental exposure biomarkers. In this study, we develop and evaluate a supervised machine learning classification framework that integrates heterogeneous demographic, anthropometric, clinical, behavioral, and environmental exposure features to classify physician-diagnosed diabetes using data from the National Health and Nutrition Examination Survey (NHANES). We analyzed NHANES 2017–2018 data for adults aged ≥18 years, addressed missingness using Multiple Imputation by Chained Equations, and corrected class imbalance via the Synthetic Minority Oversampling Technique. Model performance was evaluated using stratified ten-fold cross-validation across eight supervised classifiers: logistic regression, random forest, XGBoost, support vector machine, multilayer perceptron neural network (artificial neural network), k-nearest neighbors, naïve Bayes, and classification tree. Random Forest and XGBoost performed best on the balanced dataset, with ROC AUC values of 0.891 and 0.885, respectively, after imputation and oversampling. Feature importance analysis indicated that age, household income, and waist circumference contributed most strongly to diabetes classification. To assess out-of-sample generalization, we conducted an independent 80/20 hold-out evaluation. XGBoost achieved the highest overall accuracy and F1-score, whereas random forest attained the greatest sensitivity, demonstrating stable performance beyond cross-validation. These results indicate that incorporating environmental exposure biomarkers alongside clinical and metabolic features yields improved classification performance for physician-diagnosed diabetes. The findings support the inclusion of chemical exposure variables in population-level diabetes classification and underscore the value of integrating heterogeneous feature sets in machine learning-based risk stratification. Full article

Advances in plant nutrition have driven substantial progress in modern fertilization technologies. Nevertheless, excessive chemical fertilizer application, low nutrient-use efficiency, and the resulting environmental pollution remain widespread. We have reviewed the research progress and existing limitations in the field of plant nutrition and fertilization technology. Based on the traditional plant nutrition diagnosis and integrating visual diagnosis methods, this study explores the intrinsic relationship between plant growth status, nutrient supply conditions, and crop yield and proposed the concept of “status nutrition”. Variations in environmental nutrient conditions lead plants to exhibit distinct growth status in terms of vigor and phenotype. We define the plant nutritional status reflected by this growth status as “status nutrition”. Based on growth characteristics, plant growth status can be classified as weak, normal, or vigorous, corresponding to deficient, appropriate, and excessive environmental nutrient supply, respectively. Guided by this concept, an innovative rice “extremely dense planting” technology is integrated by increasing planting density, eliminating tiller-stage fertilization, and optimizing nitrogen management. The technology adapts to growth status with low nutrient demand, coordinates population growth and main-stem panicle formation, and achieves high yield with reduced fertilizer inputs. Further research is needed on the nutrient metabolism mechanisms of plants under different growth statuses and the growth status grading system. The promotion of “extremely dense planting” is constrained by crop variety traits and soil fertility, and its parameters urgently need to be optimized. Overall, the framework of “status nutrition” provides important theoretical support for the development and application of crop high-yield cultivation technologies. Full article

This study aimed to develop a non-invasive blood glucose estimation method by integrating wearable multimodal signals, including photoplethysmography (PPG), electrodermal activity (EDA), and skin temperature (ST), with food log–derived nutritional features, and to validate its clinical reliability. We analyzed data from 16 adults who underwent continuous glucose monitoring (CGM) while multimodal physiological signals were collected over 8–10 consecutive days, yielding more over 20,000 paired samples. Features from food logs and physiological signals were extracted, followed by feature selection using Boruta and minimum Redundancy Maximum Relevance (mRMR). Five machine learning models were trained and evaluated using five-fold cross-validation. Food log features alone demonstrated stronger predictive power than unimodal physiological signals. The fusion of nutritional, physiological, and temporal features achieved the best accuracy using LightGBM, reducing the RMSE to 12.9 mg/dL, with a MARD of 7.9%, a MAE of 8.82 mg/dL, and R² of 0.69. SHapley Additive exPlanations (SHAP) analysis revealed that 24-h carbohydrate and sugar intake, time since last meal, and short-term EDA features were the most influential predictors. By integrating multimodal wearable and dietary information, the proposed framework significantly enhances non-invasive glucose estimation. The interpretable LightGBM model demonstrates promising clinical utility for continuous monitoring and early dysglycemia management. Full article

Bentonite is a multifunctional material widely used in industry, agriculture, food processing, and medicine due to its strong binding and absorption properties. This study investigates the effects of bentonite pre-treatment at different concentrations (0.5–5%) on soybean sprout growth and nutritional quality. Moderate levels, particularly 1–3% (BP-1 and BP-3), significantly increased sprout yield (up to 16.1%) and vitamin C content (up to 18.91 mg/100 g FW), while maintaining desirable moisture and visual quality. Color evaluation showed higher yellowness (b*), suggesting improved consumer appeal. Mineral profiling indicated substantial enhancement of essential minerals across treatments, with the highest total mineral content recorded in the BP-5 group. Phosphorus, potassium, copper, and iron were notably enriched; however, elevated copper and reduced zinc at higher concentrations indicate potential nutritional risk. Isoflavone analysis revealed increased total isoflavones, especially glucoside forms such as daidzin and genistin, while aglycones like genistein decreased, reflecting bentonite’s selective influence on isoflavone metabolism. Antioxidant properties—including DPPH scavenging capacity, total polyphenols, flavonoids, and SOD-like activity—were significantly enhanced. Amino acid profiling also showed increases in essential amino acids, including methionine and valine, along with higher γ-aminobutyric acid (GABA). Overall, bentonite demonstrates strong potential as a natural additive for improving soybean sprout productivity and functional quality, with the most favorable outcomes observed at 1–3% concentrations. Full article

Marine by-products represent an important source of bioactive lipids with potential applications in nutraceuticals and functional foods. This study provides a biochemical and lipidomic characterization of oils derived from sardine, monkfish, grey mullet roe, squid, and anchovy by-products, assessing how the extraction method influences their lipid and antioxidant profiles. Fatty acids were quantified by GC-FID, antioxidant compounds by HPLC-DAD, and untargeted lipidomics by TIMS-HRMS. A total of 228 lipid species were identified, predominantly triglycerides (TGs) and diglycerides (DGs), accounting for approximately 69% of the annotated lipidome. Grey mullet roe oils exhibited the highest levels of long-chain PUFAs (EPA, DHA) and antioxidants (α-tocopherol 205–469 mg/Kg, lutein 10–125 mg/Kg, and squalene 1004–6049 mg/Kg), whereas squid oils showed high n-3/n-6 proportions. The extraction method strongly affected lipid integrity. Supercritical CO₂ extraction with ethanol (SFE–SE) preserved the greatest proportion of PUFA-rich TGs, yielding ~27–28 g EPA + DHA per 100 g oil, while wet reduction and mechanical pressing produced lower PUFA levels (~22 g/100 g) and increased hydrolysis/oxidation-associated lipids. PCA and PLS-DA revealed clear clustering driven by species and extraction class, with PUFA-containing TGs and DGs identified as major discriminating lipids. These results highlight the critical role of extraction conditions in determining the nutritional and functional value of marine oils and support the valorization of marine by-products in high-value applications. Full article

Glycyrrhiza pallidiflora Maxim., a perennial legume with high biomass yield and good nutritional value, has potential as a forage resource. This study examined how mixing G. pallidiflora (C) with Leymus chinensis (Y) at varying ratios (C10Y0, C9Y1, C8Y2, C7Y3, C6Y4) affects silage fermentation, chemical composition, and microbial community structure. All treatments were inoculated with Lactiplantibacillus plantarum (1 × 10⁶ CFU/g fresh weight) and ensiled for 120 days. The results indicated that mixed silages markedly improved overall fermentation quality compared to the sole C silage (C10Y0). These mixed silages exhibited superior lactic acid (LA) concentrations, lower pH. Bacterial community profiling revealed that the addition of Y shifted the microbiota from a diverse community to one dominated by Lactobacillus. Although the C6Y4 and C7Y3 groups exhibited lower pH, they showed significantly elevated NH₃-N contents, while their crude protein contents and the relative abundances of Lactobacillus were both lower than those of the C9Y1 and C8Y2 groups. Considering the core requirements of comprehensive quality, the mixing ratios of 9:1 (C9Y1) and 8:2 (C8Y2) demonstrated the optimal effects: at these ratios, the silage maintained a CP content of 12.84–14.48% DM, with NDF and ADF contents stabilized at 47.55–51.09% DM and 33.67–34.14% DM, respectively, and DM content of 28.85–31.32%; in terms of fermentation quality, the pH value decreased from 4.85 in the sole C silage (C10Y0) to 4.04–4.11, the LA content increased from 13.91 g/kg DM to 28.86–30.87 g/kg DM, the LA/AA ratio rose from 1.31 to 3.37–3.97, and the NH₃-N content was reduced by 0.56–0.96% TN compared to the C10Y0 (decreasing to 4.16–4.45% TN), effectively inhibiting protein degradation; at the microbial level, the LAB count reached 9.03–9.05 log₁₀ CFU/g FM, an increase of 2.12–2.14 compared to the C10Y0, with a relative abundance exceeding 80%, successfully suppressing the proliferation of undesirable bacteria such as Raoultella and Weissella and ensuring fermentation stability. This provides technical support for utilizing this plant as a viable alternative forage resource. Full article

The increasing demand for sustainable, nutrient-dense plant-based foods has intensified interest in functional ingredients that enhance nutritional quality. This study developed plant-based patties by partially replacing texturized pea protein with chia seed powder (CSP; Salvia hispanica L.) and evaluated their quality during 20 days of refrigerated storage (4 °C) under nitrogen-flushed packaging. Six formulations (F1–F6) containing 0–25% CSP were evaluated for physicochemical properties, lipid oxidation, and nutritional composition. Based on an optimal balance of texture, cooking yield, antioxidant capacity, and nutritional enhancement, the formulation containing 20% CSP was selected for further analyses. Proximate analysis revealed significant increases in protein (18–21%), fat (9–12%), and ash (2–3%) contents, accompanied by a slight reduction in moisture. All formulations maintained a stable pH throughout storage. Lipid oxidation increased gradually from 0.10–0.17 to 0.89–1.10 mg MDA/kg over 20 days but remained within acceptable limits. Fatty acid profiling indicated enhanced polyunsaturated fatty acids, particularly omega-3 and omega-6. Amino acid analysis showed elevated levels of key amino acids, including glutamic acid, aspartic acid, arginine, leucine, and lysine. Overall, patties containing 20% CSP exhibited improved nutritional quality and satisfactory oxidative stability, highlighting CSP as a promising functional ingredient for plant-based meat alternatives. Full article